Lead Software Engineer

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank Payments Technology team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. Job responsibilities • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems • Develops secure and high-quality production code, and reviews and debugs code written by others • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team. • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation. • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems • Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture Required qualifications, capabilities, and skills • Formal training or certification on software engineering concepts and 5+ years applied experience • Java and Spring Boot • Microservice design: service boundaries, API contracts and versioning, idempotency, and resilience (timeouts, retries, circuit breakers). • Oracle and JPA performance: N+1 queries, indexing, connection pools, transaction boundaries, and Liquibase migration strategy with rollback. • Observability and production ownership: SLOs, alerting, tracing, and incident and root-cause leadership. • Testing and quality gates: unit, integration and contract tests, with coverage and Sonar standards. Proficient in all aspects of the Software Development Life Cycle • Hands-on practical experience delivering system design, application development, testing, and operational stability • Advanced in one or more programming language(s) • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security. • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices • Preferred qualifications, capabilities, and skills • Trade finance and architecture: Trade finance domain knowledge; event-driven design with Kafka or MQ and the outbox pattern. • Frontend and data: React/TypeScript, Salt design system, micro-frontends behind the proxy, and modern alternatives to Jasper for reporting and analytics. • Cloud-native delivery: AWS or private cloud, Terraform/IaC, Docker, Kubernetes/Kustomize, CI/CD, blue-green or canary deployments, and multi-environment configuration. • Resilience and performance: Load testing, capacity planning, DR and BCP design, and multi-region or active-active setups. • Security, AI, and cost: OAuth2/OIDC/ADFS, JWT, session management, least privilege, OWASP, secrets handling, CVE/FARM remediation and dependency currency; governed use of Copilot-style tools; FinOps and cost optimisation.